Evaluation of the ERA5 Significant Wave Height against NDBC Buoy Data from 1979 to 2019

2021 ◽  
pp. 1-15
Author(s):  
Jichao Wang ◽  
Yue Wang
Keyword(s):  
Wave Height ◽  
Significant Wave Height ◽  
Significant Wave ◽  
Buoy Data

The validation of HY-2 altimeter measurements of a significant wave height based on buoy data

2013 ◽  
Vol 32 (11) ◽  
pp. 87-90 ◽  
Author(s):  
Jichao Wang ◽  
Jie Zhang ◽  
Jungang Yang
Keyword(s):  
Wave Height ◽  
Significant Wave Height ◽  
Significant Wave ◽  
Buoy Data

scholarly journals Wave Observations from Central California: SeaSonde Systems andIn SituWave Buoys

2011 ◽  
Vol 2011 ◽  
pp. 1-18 ◽  
Author(s):  
Regan M. Long ◽  
Don Barrick ◽  
John L. Largier ◽  
Newell Garfield
Keyword(s):  
Wave Height ◽  
Significant Wave Height ◽  
Strong Correlations ◽  
California Coast ◽  
Central California ◽  
Significant Wave ◽  
Wave Data ◽  
Reliable Source ◽  
Buoy Data

Wave data from five 12-13 MHz SeaSondes radars along the central California coast were analyzed to evaluate the utility of operational wave parameters, including significant wave height, period, and direction. Data from fourin situwave buoys served to verify SeaSonde data and independently corroborate wave variability. Hourly averaged measurements spanned distance is 150 km alongshore × 45 km offshore. Individual SeaSondes showed statistically insignificant variation over 27 km in range. Wave height inter-comparisons between regional buoys exhibit strong correlations, approximately 0.93, and RMS differences less than 50 cm over the region. SeaSonde-derived wave data were compared to nearby buoys over timescales from 15 to 26 months, and revealed wave height correlations and mean RMS difference of 53 cm. Results showed that height RMS differences are a percentage of significant wave height, rather than being constant independent of sea state. Period and directions compared favorably among radars, buoys, and the CDIP model. Results presented here suggest that SeaSondes are a reliable source of wave information. Supported by buoy data, they also reveal minimal spatial variation in significant wave height, period, and direction in coastal waters from ~45 km × ~150 km in this region of the central California coast. Small differences are explained by sheltering from coastal promontories, and cutoff boundaries in the case of the radars.

Directional Return Period of Severe Storms Off Italian Coasts

2006 ◽  
Author(s):  
Felice Arena ◽  
Saveria Meduri ◽  
Diego Pavone ◽  
Alessandra Romolo
Keyword(s):  
Wave Height ◽  
Return Period ◽  
Significant Wave Height ◽  
Severe Storms ◽  
Significant Wave ◽  
Wave Measurement ◽  
Directional Analysis ◽  
Italian Coasts ◽  
Buoy Data

The paper proposes the directional analysis of the severest storms recorded by the Italian Wave Measurement Network (RON). For this purpose the buoy data have been processed and all the storms have been selected; for the strongest storms, the direction of the sea states, which form them, has been analyzed. The directional return period of sea storms in which the maximum significant wave height exceeds a threshold is then obtained, by applying the ETS model. It is found that, for the prediction of extreme storms off Italy, it is possible to assume the duration of storms constant, with an error smaller than 4%.

Comparison of ECMWF Significant Wave Height Forecasts in the China Sea with Buoy Data

2019 ◽  
Vol 34 (6) ◽  
pp. 1693-1704 ◽  
Author(s):  
Juanjuan Wang ◽  
Benxia Li ◽  
Zhiyi Gao ◽  
Jiuke Wang
Keyword(s):  
Wave Height ◽  
Water Depth ◽  
Significant Wave Height ◽  
Monitoring Network ◽  
Taiwan Strait ◽  
Cold Air ◽  
Significant Wave ◽  
China Sea ◽  
Buoy Data ◽  
Ocean Monitoring

Abstract This paper focuses on a comprehensive comparison of the European Centre for Medium-Range Weather Forecasts (ECMWF) significant wave height (SWH) forecasts with buoy data in the China Sea, and analysis of accuracy characteristics varying with related variables (SWH, water depth, and distance from shore) and different scenarios (each month, different sea area, and typhoon- and cold air activity–induced waves). This is the first time that observations from the Chinese Ocean Monitoring Network have been used to verify ECMWF wave forecasts in the China Sea. Two years’ worth of data from 24 hydrometeorological buoys are used. The comparison shows good accuracy and predictive stability of SWH forecasts for the Chinese buoys, which is consistent with Korean and global buoys. However, the accuracy in the Bohai Sea and Taiwan Strait is worse than that in the South and East China Sea. SWH forecasts for QF206 in the southern Taiwan Strait have systematically underestimated observations, which may be mainly due to the coarse resolution of wave forecasts. Besides, forecasts underestimate observations when 1.5 m < SWH ≤ 6.5 m. The accuracy and predictive stability in spring and summer are worse than those in winter, especially in April, which is the worst in 12 months. The accuracy increases with water depth and distance from shore. During typhoon conditions, the accuracy is worse than during cold air conditions.

scholarly journals Significant Wave Height Estimation from Joint CYGNSS DDMA and LES Observations

Sensors ◽  
2021 ◽  
Vol 21 (18) ◽  
pp. 6123
Author(s):  
Shuai Yang ◽  
Shuanggen Jin ◽  
Yan Jia ◽  
Mingda Ye
Keyword(s):  
Correlation Coefficient ◽  
Wave Height ◽  
Temporal Resolution ◽  
Global Navigation Satellite System ◽  
Significant Wave Height ◽  
Satellite System ◽  
Navigation Satellite ◽  
Significant Wave ◽  
Global Navigation Satellite ◽  
Buoy Data

The significant wave height (SWH) of oceans is the main parameter in describing the sea state, which has been widely used in the establishment of ocean process models and the field of navigation and transportation. However, traditional methods such as satellite radar altimeters and buoys cannot achieve SWH estimations with high spatial and temporal resolution. Recently, the spaceborne Global Navigation Satellite System reflectometry (GNSS-R) has provided an opportunity to estimate SWH with a rapid global coverage and high temporal resolution observations, particularly with the Cyclone Global Navigation Satellite System (CYGNSS) mission. In this paper, SWH was estimated using the polynomial function relationship between SWH from ERA5 and Delay-Doppler Map Average (DDMA) as well as Leading Edge Slope (LES) from CYGNSS data. Then, the SWH estimated from CYGNSS data was validated by ERA-Interim data, AVISO data, and buoy data. The results showed that the average correlation coefficient of CYGNSS SWH was 0.945, and the average RMSE was 0.257 m when compared to the ERA-Interim SWH data. The RMSE was 0.423 m and the correlation coefficient was 0.849 when compared with the AVISO SWH. The correlation coefficient with the buoy data was 0.907, and the RMSE was 0.247 m. This method can provide suitable SWH estimation data for ocean dynamics research and ocean environment prediction.

Joint Calibration of Multiplatform Altimeter Measurements of Wind Speed and Wave Height over the Past 20 Years

2009 ◽  
Vol 26 (12) ◽  
pp. 2549-2564 ◽  
Author(s):  
S. Zieger ◽  
J. Vinoth ◽  
I. R. Young
Keyword(s):  
Wind Speed ◽  
Wave Height ◽  
Significant Wave Height ◽  
Extended Period ◽  
Cross Sectional ◽  
Significant Wave ◽  
Global Coverage ◽  
Ocean Topography ◽  
Buoy Data

Abstract Since 1985, for a period of more than 23 yr, seven altimeter missions have provided global coverage of significant wave height and wind speed. This study undertakes a long-term analysis of the accuracy and stability of altimeter-derived values of significant wave height and wind speed from the following satellites: European Remote Sensing-1 (ERS-1), ERS-2, Environmental Satellite (Envisat), Geosat, Geosat Follow-On (GFO), Jason-1, and the Ocean Topography Experiment (TOPEX). This study is a necessary step in developing a quality-controlled and fully calibrated and validated dataset from the combined satellites. Calibration of all altimeters is performed against National Oceanographic Data Center (NODC) buoy data over the extended period. These calibrations are validated using intercomparisons between satellite missions at crossover ground points. This analysis shows that, for a number of the satellites, small “step like” changes occur during the missions. These inconsistencies are removed by subdividing these missions and undertaking a partial calibration for each section of the mission. The analysis also highlights that care is necessary when attempting to apply relationships between radar cross section and wind speed derived for one altimeter to other platforms. Before undertaking such steps, it is first necessary to apply a platform-specific radar cross-sectional offset to the data.

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